COVID-19. Part 4 — The real fatality ratio, and what it means

[Updated 23 April 2021. In red]

In parts 1, 2, and 3 we discovered that the ‘announced’ fatality ratio average was 3.4%.

The truth is that it was lower than that: much much lower.  Professor John Ioannidis — probably the world’s most cited medical researcher, and a renowned expert on the evaluation of scientific evidence — has, ever since the alarm was sounded, called for, and even participated in producing, an estimate of the ratio on a basis of rigorous science.  His latest estimate, published by the World Health Organisation (WHO) and now widely accepted as reasonably accurate, is 0.23% — less than a fourteenth of the ratio that was paraded by the media and various health spokespersons for the affair’s first nine months.

If you search, you will find other estimates.  Ioannidis himself included in his analysis estimates that ranged from 0.0% to 1.63%.  The median was 0.23%.  He also pointed out that most of the estimates in his analysis were from locations with higher COVID mortality than the global average, and that the true global ratio may therefore be substantially lower.

Naturally, the fatality ratio varied considerably across age groups.  In people younger than 70 years, the median was 0.05% — one seventieth (1/70th) of the original estimate paraded to us for so long.

You will come across much heated debate about these estimates — Ioannidis himself was pilloried considerably for his work in this area.  This is understandable, as the new estimates were a substantial downward revision of the very frightening parameter on which our initial actions were largely based.  Many reputations hung in the balance, and emotions were consequently high.  The drastic measures supported by some scientists and imposed by almost all governments — social distancing, mask wearing, business closures, stay-at-home orders, no visitors for the elderly — all arose from the initially high estimate of the fatality ratio.  Thankfully, some of the heated reluctance has dissipated in recent months, and the revised, more accurate estimates are now widely accepted.

What does it mean?

So we overestimated, substantially.  But what does the figure mean anyway?  Knowing that 0.23% of those who had antibodies to the virus died at some point later may tell us very little, for the simple reason that of the rest of the population — i.e., of those who were not infected — a possibly similar proportion died.

In Australia, somewhere between 0.6% and 0.7% of the population dies each year.  But that’s one of the lowest rates in the developed world.  In the U.S.A., the figure approaches 1%.  Countries in the European Union also average 1%.  Many of them exceed that rate — e.g. Hungary, Estonia, Belgium, Belarus, Croatia, Czech Republic, Germany, and Greece.  The likes of Latvia, Lithuania, and Bulgaria lose a whopping 1.5% of their populations each year.

Why do these people die?  Because everybody dies at some time.  And the primary reason the rate is higher in some countries than in others is not that some countries are more developed or are safer.  It’s primarily because those countries have an older population, and death rates are much higher in older populations.  For instance, most developed countries lose around 15% of those aged over 85 every year.

So what does it mean, to say that we lost 0.23% of those who were at some point infected by the virus?

Your guess is as good as mine, but I’d say the answer is probably very little.

[UPDATE 23 April 2021. Since this post was published, a more recent estimate from Ioannidis, based on multiple systematic evaluations and published just this month, revised the fatality ratio down to only 0.15% less than one twentieth of the original estimate!]

In addition to those already highlighted in this series, there are many more reasons to disregard all of the covid-specific statistics we’ve been fed.  In summary, it would appear that:

  1. The test we’ve been using to identify cases has been so unreliable that experts suggest that almost all of the cases identified are likely to have been false positives.
  2. The virus has never been satisfactorily demonstrated to cause any illness whatsoever.
  3. The virus has never even been satisfactorily isolated.

I’ll leave you to research those further if you’re so inclined.  There are many many publicly available expert articles and videos on the internet that cover these issues.

The problem with over-reacting

At the start of this whole fiasco, many tried to anticipate government recommendations — sporting clubs, recreational groups, and meeting places were the first to buckle, curbing normal procedures and, in some cases, closing up altogether, well before the government recommended anything of the sort.  They wanted to get ahead of the curve and be seen as socially responsible.  Understandably, businesses acted later.  They had to look after the incomes of their employees, as well as their own.

I served on the management committee of a sporting club at the time.  Some in that committee argued that we needed to join the bandwagon and impose restrictions prematurely.  I argued the opposite.

In my view, concerns of a pandemic were hypothetical.  The only threats that we knew our members faced were panic and isolation.  If we were to shut down our service or introduce other dramatic changes, how might that affect our members, many of whom were elderly or otherwise vulnerable?

Apart from social isolation — something huge in itself — the effect of the panic that such moves might generate is difficult to quantify.  After all, it would amount to announcing that we were in the midst of a threat so dire that it demanded shutting down activities that have been a fixture for all of someone’s life.  That’s no small thing, and would no doubt suggest that the threat was very real and very large, particularly for the elderly.  Imagine that you’re over 80 and awake one morning with a tickle in your throat.  Time to get your affairs in order?

I predicted that if the restrictions (and the associated fear campaign) went ahead full tilt, as it turned out they did, many would die as a result; and, of course, those deaths would be focused on the most vulnerable: mainly the elderly, and especially those with pre-existing health problems such as heart disease.

We all understand that the elderly are statistically more likely to die — at any time — simply because of their age.  So we expect them to feature heavily in COVID-19 death statistics.  And they do.  It may interest you to know that the median age of COVID-19 fatalities in the U.K. is 81 for males and 85 for females — exactly the same as the median age of all fatalities.  So are the quoted ‘COVID’ deaths simply just deaths?  Would they have occurred even if COVID had not existed?  I aim in the next instalment to shed light on these questions.

In Parts 1, 2, and 3 we explored the basis on which COVID-19 was declared a pandemic and on which we systematically shredded our communities’ economic and social structures.  In the current instalment, we’ve shone a spotlight on just how inaccurate important estimates may be, when made in haste and with no solid foundation.  We’ve also seen how even the idea of evaluating things in the way that we did was fraught with traps and unknowns.

In the next piece, we’ll look at the only dependable way to gauge whether there was a problem and, if so, how big it was: changes in mortality.

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